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矿物油饱和烃和芳烃定量分析:单维及二维方法。

Mineral oil saturated and aromatic hydrocarbons quantification: Mono- and two-dimensional approaches.

机构信息

Analytical Chemistry Lab, Gembloux Agro-Bio Tech, University of Liège, Gembloux, 5030, Belgium.

LECO European Application and Technology Center (EATC), Berlin, Germany.

出版信息

J Chromatogr A. 2021 Apr 26;1643:462044. doi: 10.1016/j.chroma.2021.462044. Epub 2021 Mar 9.

Abstract

The determination of the level of mineral oil contamination in foods is a well-known problem. This class of contaminants is generally divided into mineral oil saturated and aromatic hydrocarbons with different toxicological relevance and analytical challenges. Among the many challenges, data interpretation and integration represent an important source of uncertainty in the results provided by different laboratories leading to a variation evaluated on the order of 20%. The use of multidimensional comprehensive gas chromatography (GC × GC) has been proposed to support the data interpretation but the integration and the reliability of the results using this methodology has never been systematically evaluated. The aim of this work was to assess the integration and quantification performance of a two-dimensional (2D) software. The data were generated using a novel, completely automated platform, namely LC-GC × GC coupled to dual detectors, i.e., time-of-flight mass spectrometer (MS) and flame ionization detector (FID). From a systematic study of the failures of the two-dimensional quantification approach a novel solution was proposed for simplifying and automating the entire process. The novel algorithm was tested on ad hoc created samples (i.e. a paraffin mixture added of n-alkanes) and real-world samples proving the agreement of the results obtained by LC-GC × GC and the traditional mono-dimensional approach. Moreover, the benefits of using an entirely integrated platform were emphasized, particularly regarding the identity confirmation capability of the MS data, which can be easily translated into the 2D FID quantification feature.

摘要

食品中矿物油污染水平的测定是一个众所周知的问题。这类污染物通常分为矿物油饱和烃和芳烃,具有不同的毒理学相关性和分析挑战。在众多挑战中,数据解释和整合是不同实验室提供的结果中不确定性的一个重要来源,导致评估变化在 20%左右。多维全二维气相色谱(GC×GC)的使用已被提议用于支持数据解释,但使用这种方法的整合和结果的可靠性从未得到系统评估。本工作的目的是评估二维(2D)软件的整合和定量性能。数据是使用一种新颖的、完全自动化的平台生成的,即 LC-GC×GC 与双检测器(飞行时间质谱仪(MS)和火焰电离检测器(FID))耦合。通过对二维定量方法的失败进行系统研究,提出了一种简化和自动化整个过程的新方法。该新算法在专门创建的样品(即添加正构烷烃的石蜡混合物)和实际样品上进行了测试,证明了 LC-GC×GC 和传统单维方法获得的结果的一致性。此外,还强调了使用完全集成平台的好处,特别是 MS 数据的身份确认能力,这可以很容易地转化为 2D FID 定量功能。

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